P856: A SINGLE-CELL FUNCTIONAL PRECISION MEDICINE LANDSCAPE OF MULTIPLE MYELOMA
Authors: K. Kropivsek, P. Kachel, S. Goetze, R. Wegmann, Y. Severin, B. D. Hale, Y. Festl, J. Mena, A. van Drogen, N. Dietliker, J. Tchinda, B. Wollscheid, M. G. Manz, B. Snijder
Journal: HemaSphere (2022)

Background: Multiple myeloma (MM) is a cancer of plasma cells, defined by complex genetics and extensive intra- and inter-patient heterogeneity. Despite improved patient survival driven by a plethora of treatment options, the disease remains incurable. Molecularly-guided precision medicine to individualize treatment strategies in MM has had limited success, in part due to the genetic and molecular complexity of the disease. Functional precision medicine, a complementary approach in which patient treatment is guided by the ex vivo drug response of patient cells, has not yet been evaluated for MM systematically. Aims: Our observational study has two aims: 1) To evaluate single-cell resolved functional precision medicine (also called Pharmacoscopy) as a way to tailor treatment for individual MM patients; 2) To identify new treatment options for, and improve our molecular understanding of, MM. Methods: In our observational clinical study, image-based ex vivo drug screening (Pharmacoscopy; PCY) measured the single-cell level responses to drug and immunotherapy combinations for 138 patient samples from 98 patients covering all stages of the disease. Single-cell morphologies are analyzed by deep convolutional neural networks, quantifying the cellular composition and morphological myeloma heterogeneity at time of sampling. PCY data is integrated with 1) sample-matched proteomics of purified cell subpopulations, 2) bone marrow serum cytokine profiling, as well as with 3) patient-matched genetics and clinical data. Lastly, ex vivo drug sensitivities are matched to clinical responses. Results: Our large-scale single-cell morphological characterization of Multiple Myeloma samples reveals three reoccurring cell community modes, which we call PhenoGroups (PGs). These PGs represent different disease stages, with both genetic and inflammatory associations, independently confirmed by orthogonal data. The ex vivo responses to 61 existing and novel therapeutic strategies (ranging from single drugs to quadruple drug combinations) reveal considerable differences in patients’ ex vivo responses to the same treatments. Integration with proteotype data discovers the comprehensive molecular network underlying variable drug sensitivities, recovering known regulators of drug response in myeloma and identifying new possible mechanisms of action. Furthermore, integration with genetics and clinical characteristics across patients recovers known biomarkers, e.g. proteasome inhibitor resistance for TP53 mutant patient samples, and proposes novel biomarkers for individualized patient treatments. The strongest predictor of ex vivo drug sensitivity is the sample composition as captured by the PhenoGroups, which we find is also reflected in the clinical course. Finally, longitudinal follow-up and Kaplan-Meier analyses confirm that Pharmacoscopy-measured drug responses are significantly predictive of the clinical response of patients (Figure 1). Image:Summary/Conclusion: Our single-cell functional precision medicine platform (Pharmacoscopy) combined with patient-matched OMICs provides molecular and clinical insights into existing and novel treatment strategies for MM patients. Furthermore, Pharmacoscopy is significantly predictive of clinical response in MM, warranting further clinical investigation.